Download Record

Author

Date

Advisor

Second Reader

Metadata

Abstract

Battle management decision making requires a composite picture of the
environment, including identification of moving and stationary "targets". The current
state of technology allows large volumes of data to be gathered from multiple sources.
Target kinematics and identity features must be derived through fusion of the data.
Initial assignment and maintenance of track numbers, the identifying labels, may lead to
ambiguity in command and control information management. The problem is discussed
in terms of data fusion in a multiple sensor environment, giving particular emphasis to
managing track ED numbers in representative architectures. An overview of data fusion
provides a framework for the problem of track ID's. A Centralized Architecture,
Distributed Architecture, and two Hybrid Architectures are developed focusing on design
tradeoffs. System evaluation using the Analytic Hierarchy Process furnishes the reader
an illustration of a process which might be used to select an optimal architecture. This
research does not attempt to propose a specific design, but identifies several key criteria
which must be evaluated and suggests a framework for comparative analysis.

The lack of legal uniformity in the National Network of Fusion Centers, or National Network, is not a simple problem, and there is no simple solution; however, operating in a network with 79 fusion centers and 54 different ...

This thesis explores the use of neural networks to perform multisensor data fusion for Vessel Traffic Services (VTS). It begins with a detailed study of the VTS system in order to identify the type of input data and other ...

Different sensors exploit different regions of the electromagnetic spectrum; therefore, a multi-sensor image fusion system can take full advantage of the complementary capabilities of individual sensors in the suit; to ...